There are shared values, beliefs, and norms around psychological safety, continual improvement, and using data to inform practice.

Learning culture is a prominent theory in healthcare, especially as systems press forward to become “learning systems” (Ashok et al., 2018; Dy et al., 2015; Harrison & Shortell, 2021; Institute of Medicine (IOM), 2013). Ideally, continuous learning is occurring throughout the Inner Setting with visible evidence of engaged process improvement (including historical evidence of previous change initiatives (Breimaier et al., 2015)), use of data to inform change, and the necessary relational environment (Edmondson, 2012; Lapré & Nembhard, 2011; Miake-Lye et al., 2020). Shared values, beliefs, and norms around psychological safety, continual improvement, and using data to inform practice (Guise et al., 2018; Harrison & Shortell, 2021; Institute of Medicine (IOM), 2013; Lapré & Nembhard, 2011) support and enable employee skill development through increased experience implementing innovations (Breimaier et al., 2015). This culture creates a collective learning mindset (Edmondson, 2012) and increases the setting’s absorptive capacity for new knowledge and methods (Greenhalgh, Robert, et al., 2004).

The original CFIR’s learning climate construct has been moved under Culture in the updated CFIR because of the lack of agreement on culture versus climate concepts. As with the other Culture subconstructs, Learning-Centeredness can be assessed as a broad Inner Setting culture or as a specific micro-system climate.

The original CFIR elaborated further on this construct, stating that learning-centeredness manifests through several behaviors and perceptions: a) leaders express their own fallibility and need for team member assistance and input; b) team members feel that they are essential, valued, and knowledgeable partners in implementation; c) individuals feel psychologically safe to try new methods; and d) there is sufficient time and space for reflective thinking and evaluation (Klein et al., 2001; Leeman et al., 2007; Nembhard & Edmonson, 2006).

The degree to which an organization demonstrates “learning” will vary across sub-groups, and manifestations of these attributes may have a stronger influence than a general measure of learning in the setting more broadly (Edmondson et al., 2001). The literature on team learning has emphasized the setting’s role in creating the climate to enable learning and fostering collaboration within and between cross-disciplinary teams (Edmondson, 2002) (also see Relational Connections and Process: Teaming).

However, there is no agreement on precisely how to operationalize this construct. Despite this, we can make some generalizations. In a positive learning climate, individuals are not constrained by failure and psychological safety is promoted. Psychological safety has predicted engagement in quality improvement work (Nembhard & Edmonson, 2006). Having the time and space for reflective thinking and evaluation (see also, Process: Reflecting and Evaluating) is another important characteristic, at least in part, because it promotes learning from past successes and failures to inform future implementations (Edmondson et al., 2001; Helfrich, Weiner, et al., 2007). Developing a culture that promotes learning is a “core property” that health care organizations need for on-going quality improvement (Ferlie & Shortell, 2001 p287). A learning culture is an important contributor for increasing absorptive capacity for new knowledge: the ability of an organization to fully assimilate innovations (Greenhalgh, Robert, et al., 2004). Greenhalgh et al. include learning organization culture within their concept of absorptive capacity of new knowledge along with existing knowledge and skills (tacit and explicit), and within proactive leadership (Greenhalgh, Robert, et al., 2004).

Qualitative coding guidelines that are aligned with the Updated CFIR will be added in the future.

Inclusion Criteria

Include statements that support (or refute) the degree to which key components of the Inner Setting exhibits collective learning.

  • “Last year we had a colossal failure in trying to change our procedure to check patients in. We met about that and we are looking forward to trying something like that again because we agreed on what we think caused the failure.”
  • “I emphasize with my team that they need to bring out any and all problems.”

Quantitative measurement instruments are available for measuring an organization’s “learning” capability (Goh & Richards, 1997; Templeton et al., 2002). Additionally, in a systematic review of quantitative measures related to implementation, Powell et al. identified two measures for learning climate (Powell et al., 2021). Using PAPERS criteria of measurement quality with an aggregate scale ranging from -9 to +36 (Lewis, Mettert, Stanick, et al., 2021), The Ramsey Learning Climate Measure (Ramsey et al., 2015) was rated the highest with a score of 6. Results indicate the need for continued development of high-quality measures.

As we become aware of additional measures, we will post them here. Please contact us with updates.

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Breimaier, H. E., Heckemann, B., Halfens, R. J. G., & Lohrmann, C. (2015). The Consolidated Framework for Implementation Research (CFIR): A useful theoretical framework for guiding and evaluating a guideline implementation process in a hospital-based nursing practice. BMC Nursing, 14(1), 43. https://doi.org/10.1186/s12912-015-0088-4.

Dorsey, C. N., Mettert, K. D., Puspitasari, A. J., Damschroder, L. J., & Lewis, C. C. (2021). A systematic review of measures of implementation players and processes: Summarizing the dearth of psychometric evidence. Implementation Research and Practice, 2, 263348952110024.

Dy, S. M., Ashok, M., Wines, R. C., & Rojas Smith, L. (2015). A Framework to Guide Implementation Research for Care Transitions Interventions: Journal for Healthcare Quality, 37(1), 41–54. https://doi.org/10.1097/01.JHQ.0000460121.06309.f9.

Edmondson, A. C. (2012). Teaming: How organizations learn, innovate, and compete in the knowledge economy. Jossey-Bass.

Edmondson, A. C., Bohmer, R. M., & Pisana, G. P. (2001). Disrupted routines: Team learning and new technology implementation in hospitals. Administrative Science Quarterly, 46(4), 685–716.

Edmondson, A. C. (2002). The Local and Variegated Nature of Learning in Organizations: A Group-Level Perspective. Organization Science, 13(2), 128–146. https://doi.org/10.1287/orsc.

Ferlie, E. B., & Shortell, S. M. (2001). Improving the quality of health care in the United Kingdom and the United States: A framework for change. Milbank Q, 79(2), 281–315.

Greenhalgh, T., Robert, G., Macfarlane, F., Bate, P., & Kyriakidou, O. (2004). Diffusion of innovations in service organizations: Systematic review and recommendations. Milbank Q, 82(4), 581–629.

Goh, S., & Richards, G. (1997). Benchmarking the learning capability of organizations. European Management Journal, 15(5), 575–583. https://doi.org/10.1016/S0263-2373(97)00036-4.

Guise, J.-M., Savitz, L. A., & Friedman, C. P. (2018). Mind the Gap: Putting Evidence into Practice in the Era of Learning Health Systems. Journal of General Internal Medicine, 33(12), 2237–2239. https://doi.org/10.1007/s11606-018-4633-1.

Harrison, M. I., & Shortell, S. M. (2021). Multi‐level analysis of the learning health system: Integrating contributions from research on organizations and implementation. Learning Health Systems, 5(2). https://doi.org/10.1002/lrh2.10226.

Helfrich, C. D., Weiner, B. J., McKinney, M. M., & Minasian, L. (2007). Determinants of implementation effectiveness: Adapting a framework for complex innovations. Med Care Res Rev, 64(3), 279–303.

Institute of Medicine (IOM). (2013). Best Care at Lower Cost: The Path to Continuously Learning Health Care in America (p. 13444). National Academies Press. https://doi.org/10.17226/13444.

Klein, K. J., Conn, A. B., & Sorra, J. S. (2001). Implementing computerized technology: An organizational analysis. Journal of Applied Psychology, 86(5), 811–824.

Lapré, M. A., & Nembhard, I. M. (2011). Inside the Organizational Learning Curve: Understanding the Organizational Learning Process. Foundations and Trends® in Technology, Information and Operations Management, 4(1), 1–103. https://doi.org/10.1561/0200000023.

Leeman, J., Baernholdt, M., & Sandelowski, M. (2007). Developing a theory-based taxonomy of methods for implementing change in practice. J Adv Nurs, 58(2), 191–200.

Lewis, C. C., Mettert, K. D., Stanick, C. F., Halko, H. M., Nolen, E. A., Powell, B. J., & Weiner, B. J. (2021). The psychometric and pragmatic evidence rating scale (PAPERS) for measure development and evaluation. Implementation Research and Practice, 2, 263348952110373. https://doi.org/10.1177/26334895211037391.

Miake-Lye, I. M., Delevan, D. M., Ganz, D. A., Mittman, B. S., & Finley, E. P. (2020). Unpacking organizational readiness for change: An updated systematic review and content analysis of assessments. BMC Health Services Research, 20(1), 106. https://doi.org/10.1186/s12913-020-4926-z.

Nembhard, I. M., & Edmondson, A. C. (2006). Making it safe: The effects of leader inclusiveness and professional status on psychological safety and improvement efforts in health care teams. Journal of Organizational Behavior, 27, 941–966.

Powell, B. J., Mettert, K. D., Dorsey, C. N., Weiner, B. J., Stanick, C. F., Lengnick-Hall, R., Ehrhart, M. G., Aarons, G. A., Barwick, M. A., Damschroder, L. J., & Lewis, C. C. (2021). Measures of organizational culture, organizational climate, and implementation climate in behavioral health: A systematic review. Implementation Research and Practice, 2, 263348952110188. https://doi.org/10.1177/26334895211018862.

Ramsey, A. T., van den Berk-Clark, C., & Patterson Silver Wolf (Adelv unegv Waya), D. A. (2015). Provider-agency fit in substance abuse treatment organizations: Implications for learning climate, morale, and evidence-based practice implementation. BMC Research Notes, 8(1), 194. https://doi.org/10.1186/s13104-015-1110-3.

Templeton, G. F., Lewis, B. R., & Snyder, C. A. (2002). Development of a measure for the organizational learning construct. Journal of Management Information Systems, 19(2), 175–218.